" Intelligent Heart Disease Prediction System Using Data Mining Techniques "

Today medical services have come a long way to treat patients with various diseases. Among the most lethal one is the heart disease problem which cannot be seen with a naked eye and comes instantly when its limitations are reached. Today diagnosing patients correctly and administering effective treatments have become quite a challenge. Poor clinical decisions may end to patient death and which cannot be afforded by the hospital as it loses its reputation. The cost to treat a patient with a heart problem is quite high and not affordable by every patient. To achieve a correct and cost effective treatment computer-based information and/or decision support Systems can be developed to do the task. Most hospitals today use some sort of hospital information systems to manage their healthcare or patient data. These systems typically generate huge amounts of data which take the form of numbers, text, charts and images. Unfortunately, these data are rarely used to support clinical decision making. There is a wealth of hidden information in these data that is largely untapped. This raises an important question: " How can we turn data into useful information that can enable healthcare practitioners to make intelligent clinical decisions? " So there is need of developing a master's project which will help practitioners predict the heart disease before it occurs.The diagnosis of diseases is a vital and intricate job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by impulsive effects. Thus the attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a valuable option.